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1  \section{Fizhi: High-end Atmospheric Physics}  \subsection{Fizhi: High-end Atmospheric Physics}
2  \label{sec:pkg:fizhi}  \label{sec:pkg:fizhi}
3  \begin{rawhtml}  \begin{rawhtml}
4  <!-- CMIREDIR:package_fizhi: -->  <!-- CMIREDIR:package_fizhi: -->
5  \end{rawhtml}  \end{rawhtml}
6  \input{texinputs/epsf.tex}  \input{texinputs/epsf.tex}
7    
8  \subsection{Introduction}  \subsubsection{Introduction}
9  The fizhi (high-end atmospheric physics) package includes a collection of state-of-the-art  The fizhi (high-end atmospheric physics) package includes a collection of state-of-the-art
10  physical parameterizations for atmospheric radiation, cumulus convection, atmospheric  physical parameterizations for atmospheric radiation, cumulus convection, atmospheric
11  boundary layer turbulence, and land surface processes.  boundary layer turbulence, and land surface processes. The collection of atmospheric
12    physics parameterizations were originally used together as part of the GEOS-3
13    (Goddard Earth Observing System-3) GCM developed at the NASA/Goddard Global Modelling
14    and Assimilation Office (GMAO).
15    
16  % *************************************************************************  % *************************************************************************
17  % *************************************************************************  % *************************************************************************
18    
19  \subsection{Equations}  \subsubsection{Equations}
20    
21  \subsubsection{Moist Convective Processes}  Moist Convective Processes:
22    
23  \paragraph{Sub-grid and Large-scale Convection}  \paragraph{Sub-grid and Large-scale Convection}
24  \label{sec:fizhi:mc}  \label{sec:fizhi:mc}
25    
26  Sub-grid scale cumulus convection is parameterized using the Relaxed Arakawa  Sub-grid scale cumulus convection is parameterized using the Relaxed Arakawa
27  Schubert (RAS) scheme of Moorthi and Suarez (1992), which is a linearized Arakawa Schubert  Schubert (RAS) scheme of \cite{moorsz:92}, which is a linearized Arakawa Schubert
28  type scheme.  RAS predicts the mass flux from an ensemble of clouds.  Each subensemble is identified  type scheme.  RAS predicts the mass flux from an ensemble of clouds.  Each subensemble is identified
29  by its entrainment rate and level of neutral bouyancy which are determined by the grid-scale properties.  by its entrainment rate and level of neutral bouyancy which are determined by the grid-scale properties.
30    
# Line 33  buoyancy. RAS assumes that the normalize Line 36  buoyancy. RAS assumes that the normalize
36  mass flux, is a linear function of height, expressed as:  mass flux, is a linear function of height, expressed as:
37  \[  \[
38  \pp{\eta(z)}{z} = \lambda \hspace{0.4cm}or\hspace{0.4cm} \pp{\eta(P^{\kappa})}{P^{\kappa}} =  \pp{\eta(z)}{z} = \lambda \hspace{0.4cm}or\hspace{0.4cm} \pp{\eta(P^{\kappa})}{P^{\kappa}} =
39  -{c_p \over {g}}\theta\lambda  -\frac{c_p}{g}\theta\lambda
40  \]  \]
41  where we have used the hydrostatic equation written in the form:  where we have used the hydrostatic equation written in the form:
42  \[  \[
43  \pp{z}{P^{\kappa}} = -{c_p \over {g}}\theta  \pp{z}{P^{\kappa}} = -\frac{c_p}{g}\theta
44  \]  \]
45    
46  The entrainment parameter, $\lambda$, characterizes a particular subensemble based on its  The entrainment parameter, $\lambda$, characterizes a particular subensemble based on its
47  detrainment level, and is obtained by assuming that the level of detrainment is the level of neutral  detrainment level, and is obtained by assuming that the level of detrainment is the level of neutral
48  buoyancy, ie., the level at which the moist static energy of the cloud, $h_c$, is equal  buoyancy, ie., the level at which the moist static energy of the cloud, $h_c$, is equal
49  to the saturation moist static energy of the environment, $h^*$.  Following Moorthi and Suarez (1992),  to the saturation moist static energy of the environment, $h^*$.  Following \cite{moorsz:92},
50  $\lambda$ may be written as  $\lambda$ may be written as
51  \[  \[
52  \lambda = { {h_B - h^*_D} \over { {c_p \over g} {\int_{P_D}^{P_B}\theta(h^*_D-h)dP^{\kappa}}} } ,  \lambda = \frac{h_B - h^*_D}{ \frac{c_p}{g} \int_{P_D}^{P_B}\theta(h^*_D-h)dP^{\kappa}},
53  \]  \]
54    
55  where the subscript $B$ refers to cloud base, and the subscript $D$ refers to the detrainment level.  where the subscript $B$ refers to cloud base, and the subscript $D$ refers to the detrainment level.
# Line 57  rate of change of cumulus kinetic energy Line 60  rate of change of cumulus kinetic energy
60  related to the buoyancy, or the difference  related to the buoyancy, or the difference
61  between the moist static energy in the cloud and in the environment:  between the moist static energy in the cloud and in the environment:
62  \[  \[
63  A = \int_{P_D}^{P_B} { {\eta \over {1 + \gamma} }  A = \int_{P_D}^{P_B} \frac{\eta}{1 + \gamma}
64  \left[ {{h_c-h^*} \over {P^{\kappa}}} \right] dP^{\kappa}}  \left[ \frac{h_c-h^*}{P^{\kappa}} \right] dP^{\kappa}
65  \]  \]
66    
67  where $\gamma$ is ${L \over {c_p}}\pp{q^*}{T}$ obtained from the Claussius Clapeyron equation,  where $\gamma$ is $\frac{L}{c_p}\pp{q^*}{T}$ obtained from the Claussius Clapeyron equation,
68  and the subscript $c$ refers to the value inside the cloud.  and the subscript $c$ refers to the value inside the cloud.
69    
70    
# Line 69  To determine the cloud base mass flux, t Line 72  To determine the cloud base mass flux, t
72  the clouds} is assumed to approximately balance the rate of change of $A$ {\em due to the generation  the clouds} is assumed to approximately balance the rate of change of $A$ {\em due to the generation
73  by the large scale}. This is the quasi-equilibrium assumption, and results in an expression for $m_B$:  by the large scale}. This is the quasi-equilibrium assumption, and results in an expression for $m_B$:
74  \[  \[
75  m_B = {{- \left.{dA \over dt} \right|_{ls}} \over K}  m_B = \frac{- \left. \frac{dA}{dt} \right|_{ls}}{K}
76  \]  \]
77    
78  where $K$ is the cloud kernel, defined as the rate of change of the cloud work function per  where $K$ is the cloud kernel, defined as the rate of change of the cloud work function per
# Line 87  and moisture budget equations to determi Line 90  and moisture budget equations to determi
90  temperature (through latent heating and compensating subsidence) and moisture (through  temperature (through latent heating and compensating subsidence) and moisture (through
91  precipitation and detrainment):  precipitation and detrainment):
92  \[  \[
93  \left.{\pp{\theta}{t}}\right|_{c} = \alpha { m_B \over {c_p P^{\kappa}}} \eta \pp{s}{p}  \left.{\pp{\theta}{t}}\right|_{c} = \alpha \frac{ m_B}{c_p P^{\kappa}} \eta \pp{s}{p}
94  \]  \]
95  and  and
96  \[  \[
97  \left.{\pp{q}{t}}\right|_{c} = \alpha { m_B \over {L}} \eta (\pp{h}{p}-\pp{s}{p})  \left.{\pp{q}{t}}\right|_{c} = \alpha \frac{ m_B}{L} \eta (\pp{h}{p}-\pp{s}{p})
98  \]  \]
99  where $\theta = {T \over P^{\kappa}}$, $P = (p/p_0)$, and $\alpha$ is the relaxation parameter.  where $\theta = \frac{T}{P^{\kappa}}$, $P = (p/p_0)$, and $\alpha$ is the relaxation parameter.
100    
101  As an approximation to a full interaction between the different allowable subensembles,  As an approximation to a full interaction between the different allowable subensembles,
102  many clouds are simulated frequently, each modifying the large scale environment some fraction  many clouds are simulated frequently, each modifying the large scale environment some fraction
# Line 101  $\alpha$ of the total adjustment. The pa Line 104  $\alpha$ of the total adjustment. The pa
104  towards equillibrium.    towards equillibrium.  
105    
106  In addition to the RAS cumulus convection scheme, the fizhi package employs a  In addition to the RAS cumulus convection scheme, the fizhi package employs a
107  Kessler-type scheme for the re-evaporation of falling rain (Sud and Molod, 1988), which  Kessler-type scheme for the re-evaporation of falling rain (\cite{sudm:88}), which
108  correspondingly adjusts the temperature assuming $h$ is conserved. RAS in its current  correspondingly adjusts the temperature assuming $h$ is conserved. RAS in its current
109  formulation assumes that all cloud water is deposited into the detrainment level as rain.  formulation assumes that all cloud water is deposited into the detrainment level as rain.
110  All of the rain is available for re-evaporation, which begins in the level below detrainment.  All of the rain is available for re-evaporation, which begins in the level below detrainment.
# Line 133  Convective cloud fractions produced by R Line 136  Convective cloud fractions produced by R
136  detrained liquid water amount given by  detrained liquid water amount given by
137    
138  \[  \[
139  F_{RAS} = \min\left[ {l_{RAS}\over l_c}, 1.0 \right]  F_{RAS} = \min\left[ \frac{l_{RAS}}{l_c}, 1.0 \right]
140  \]  \]
141    
142  where $l_c$ is an assigned critical value equal to $1.25$ g/kg.  where $l_c$ is an assigned critical value equal to $1.25$ g/kg.
143  A memory is associated with convective clouds defined by:  A memory is associated with convective clouds defined by:
144    
145  \[  \[
146  F_{RAS}^n = \min\left[ F_{RAS} + (1-{\Delta t_{RAS}\over\tau})F_{RAS}^{n-1}, 1.0 \right]  F_{RAS}^n = \min\left[ F_{RAS} + (1-\frac{\Delta t_{RAS}}{\tau})F_{RAS}^{n-1}, 1.0 \right]
147  \]  \]
148    
149  where $F_{RAS}$ is the instantanious cloud fraction and $F_{RAS}^{n-1}$ is the cloud fraction  where $F_{RAS}$ is the instantanious cloud fraction and $F_{RAS}^{n-1}$ is the cloud fraction
# Line 151  Large-scale cloudiness is defined, follo Line 154  Large-scale cloudiness is defined, follo
154  humidity:  humidity:
155    
156  \[  \[
157  F_{LS} = \min\left[ { \left( {RH-RH_c \over 1-RH_c} \right) }^2, 1.0 \right]  F_{LS} = \min\left[ { \left( \frac{RH-RH_c}{1-RH_c} \right) }^2, 1.0 \right]
158  \]  \]
159    
160  where  where
# Line 159  where Line 162  where
162  \bqa  \bqa
163  RH_c & = & 1-s(1-s)(2-\sqrt{3}+2\sqrt{3} \, s)r \nonumber \\  RH_c & = & 1-s(1-s)(2-\sqrt{3}+2\sqrt{3} \, s)r \nonumber \\
164     s & = & p/p_{surf} \nonumber \\     s & = & p/p_{surf} \nonumber \\
165     r & = & \left( {1.0-RH_{min} \over \alpha} \right) \nonumber \\     r & = & \left( \frac{1.0-RH_{min}}{\alpha} \right) \nonumber \\
166  RH_{min} & = & 0.75 \nonumber \\  RH_{min} & = & 0.75 \nonumber \\
167  \alpha & = & 0.573285 \nonumber  .  \alpha & = & 0.573285 \nonumber  .
168  \eqa  \eqa
169    
170  These cloud fractions are suppressed, however, in regions where the convective  These cloud fractions are suppressed, however, in regions where the convective
171  sub-cloud layer is conditionally unstable.  The functional form of $RH_c$ is shown in  sub-cloud layer is conditionally unstable.  The functional form of $RH_c$ is shown in
172  Figure (\ref{fig:fizhi:rhcrit}).  Figure (\ref{fig.rhcrit}).
173    
174  \begin{figure*}[htbp]  \begin{figure*}[htbp]
175    \vspace{0.4in}    \vspace{0.4in}
176    \centerline{  \epsfysize=4.0in  \epsfbox{part6/rhcrit.ps}}    \centerline{  \epsfysize=4.0in  \epsfbox{s_phys_pkgs/figs/rhcrit.ps}}
177    \vspace{0.4in}    \vspace{0.4in}
178    \caption  [Critical Relative Humidity for Clouds.]    \caption  [Critical Relative Humidity for Clouds.]
179              {Critical Relative Humidity for Clouds.}              {Critical Relative Humidity for Clouds.}
180    \label{fig:fizhi:rhcrit}    \label{fig.rhcrit}
181  \end{figure*}  \end{figure*}
182    
183  The total cloud fraction in a grid box is determined by the larger of the two cloud fractions:  The total cloud fraction in a grid box is determined by the larger of the two cloud fractions:
# Line 186  F_{CLD} = \max \left[ F_{RAS},F_{LS} \ri Line 189  F_{CLD} = \max \left[ F_{RAS},F_{LS} \ri
189  Finally, cloud fractions are time-averaged between calls to the radiation packages.  Finally, cloud fractions are time-averaged between calls to the radiation packages.
190    
191    
192  \subsubsection{Radiation}  Radiation:
193    
194  The parameterization of radiative heating in the fizhi package includes effects  The parameterization of radiative heating in the fizhi package includes effects
195  from both shortwave and longwave processes.  from both shortwave and longwave processes.
# Line 221  The solar constant value used in the pac Line 224  The solar constant value used in the pac
224  and a $CO_2$ mixing ratio of 330 ppm.  and a $CO_2$ mixing ratio of 330 ppm.
225  For the ozone mixing ratio, monthly mean zonally averaged  For the ozone mixing ratio, monthly mean zonally averaged
226  climatological values specified as a function  climatological values specified as a function
227  of latitude and height (Rosenfield, et al., 1987) are linearly interpolated to the current time.  of latitude and height (\cite{rosen:87}) are linearly interpolated to the current time.
228    
229    
230  \paragraph{Shortwave Radiation}  \paragraph{Shortwave Radiation}
# Line 231  heating due to the absoption by water va Line 234  heating due to the absoption by water va
234  clouds, and aerosols and due to the  clouds, and aerosols and due to the
235  scattering by clouds, aerosols, and gases.  scattering by clouds, aerosols, and gases.
236  The shortwave radiative processes are described by  The shortwave radiative processes are described by
237  Chou (1990,1992). This shortwave package  \cite{chou:90,chou:92}. This shortwave package
238  uses the Delta-Eddington approximation to compute the  uses the Delta-Eddington approximation to compute the
239  bulk scattering properties of a single layer following King and Harshvardhan (JAS, 1986).  bulk scattering properties of a single layer following King and Harshvardhan (JAS, 1986).
240  The transmittance and reflectance of diffuse radiation  The transmittance and reflectance of diffuse radiation
241  follow the procedures of Sagan and Pollock (JGR, 1967) and Lacis and Hansen (JAS, 1974).  follow the procedures of Sagan and Pollock (JGR, 1967) and \cite{lhans:74}.
242    
243  Highly accurate heating rate calculations are obtained through the use  Highly accurate heating rate calculations are obtained through the use
244  of an optimal grouping strategy of spectral bands.  By grouping the UV and visible regions  of an optimal grouping strategy of spectral bands.  By grouping the UV and visible regions
# Line 305  cloud cover of all the layers in the gro Line 308  cloud cover of all the layers in the gro
308  of a given layer is then scaled for both the direct (as a function of the  of a given layer is then scaled for both the direct (as a function of the
309  solar zenith angle) and diffuse beam radiation  solar zenith angle) and diffuse beam radiation
310  so that the grouped layer reflectance is the same as the original reflectance.  so that the grouped layer reflectance is the same as the original reflectance.
311  The solar flux is computed for each of the eight cloud realizations possible  The solar flux is computed for each of eight cloud realizations possible within this
 (see Figure \ref{fig:fizhi:cloud}) within this  
312  low/middle/high classification, and appropriately averaged to produce the net solar flux.  low/middle/high classification, and appropriately averaged to produce the net solar flux.
313    
 \begin{figure*}[htbp]  
   \vspace{0.4in}  
   \centerline{  \epsfysize=4.0in  %\epsfbox{part6/rhcrit.ps}  
              }  
   \vspace{0.4in}  
   \caption  {Low-Middle-High Cloud Configurations}  
   \label{fig:fizhi:cloud}  
 \end{figure*}  
   
   
314  \paragraph{Longwave Radiation}  \paragraph{Longwave Radiation}
315    
316  The longwave radiation package used in the fizhi package is thoroughly described by Chou and Suarez (1994).  The longwave radiation package used in the fizhi package is thoroughly described by \cite{chsz:94}.
317  As described in that document, IR fluxes are computed due to absorption by water vapor, carbon  As described in that document, IR fluxes are computed due to absorption by water vapor, carbon
318  dioxide, and ozone.  The spectral bands together with their absorbers and parameterization methods,  dioxide, and ozone.  The spectral bands together with their absorbers and parameterization methods,
319  configured for the fizhi package, are shown in Table \ref{tab:fizhi:longwave}.  configured for the fizhi package, are shown in Table \ref{tab:fizhi:longwave}.
# Line 357  Band & Spectral Range (cm$^{-1}$) & Abso Line 349  Band & Spectral Range (cm$^{-1}$) & Abso
349  \end{tabular}  \end{tabular}
350  \end{center}  \end{center}
351  \vspace{0.1in}  \vspace{0.1in}
352  \caption{IR Spectral Bands, Absorbers, and Parameterization Method (from Chou and Suarez, 1994)}  \caption{IR Spectral Bands, Absorbers, and Parameterization Method (from \cite{chsz:94})}
353  \label{tab:fizhi:longwave}  \label{tab:fizhi:longwave}
354  \end{table}  \end{table}
355    
# Line 417  The total optical depth in a given model Line 409  The total optical depth in a given model
409  the large-scale and sub-grid scale optical depths, normalized by the total cloud fraction in the  the large-scale and sub-grid scale optical depths, normalized by the total cloud fraction in the
410  layer:  layer:
411    
412  \[ \tau = \left( {F_{RAS} \,\,\, \tau_{RAS} + F_{LS} \,\,\, \tau_{LS} \over F_{RAS}+F_{LS} } \right) \Delta p, \]  \[ \tau = \left( \frac{F_{RAS} \,\,\, \tau_{RAS} + F_{LS} \,\,\, \tau_{LS} }{ F_{RAS}+F_{LS} } \right) \Delta p, \]
413    
414  where $F_{RAS}$ and $F_{LS}$ are the time-averaged cloud fractions associated with RAS and large-scale  where $F_{RAS}$ and $F_{LS}$ are the time-averaged cloud fractions associated with RAS and large-scale
415  processes described in Section \ref{sec:fizhi:clouds}.  processes described in Section \ref{sec:fizhi:clouds}.
# Line 428  The cloud fraction values are time-avera Line 420  The cloud fraction values are time-avera
420  hours).  Therefore, in a time-averaged sense, both convective and large-scale  hours).  Therefore, in a time-averaged sense, both convective and large-scale
421  cloudiness can exist in a given grid-box.    cloudiness can exist in a given grid-box.  
422    
423  \subsubsection{Turbulence}  \paragraph{Turbulence}:
424    
425  Turbulence is parameterized in the fizhi package to account for its contribution to the  Turbulence is parameterized in the fizhi package to account for its contribution to the
426  vertical exchange of heat, moisture, and momentum.    vertical exchange of heat, moisture, and momentum.  
427  The turbulence scheme is invoked every 30 minutes, and employs a backward-implicit iterative  The turbulence scheme is invoked every 30 minutes, and employs a backward-implicit iterative
# Line 458  Within the atmosphere, the time evolutio Line 451  Within the atmosphere, the time evolutio
451  of second turbulent moments is explicitly modeled by representing the third moments in terms of  of second turbulent moments is explicitly modeled by representing the third moments in terms of
452  the first and second moments.  This approach is known as a second-order closure modeling.  the first and second moments.  This approach is known as a second-order closure modeling.
453  To simplify and streamline the computation of the second moments, the level 2.5 assumption  To simplify and streamline the computation of the second moments, the level 2.5 assumption
454  of Mellor and Yamada (1974) and Yamada (1977) is employed, in which only the turbulent  of Mellor and Yamada (1974) and \cite{yam:77} is employed, in which only the turbulent
455  kinetic energy (TKE),  kinetic energy (TKE),
456    
457  \[ {\h}{q^2}={\overline{{u^{\prime}}^2}}+{\overline{{v^{\prime}}^2}}+{\overline{{w^{\prime}}^2}}, \]  \[ {\h}{q^2}={\overline{{u^{\prime}}^2}}+{\overline{{v^{\prime}}^2}}+{\overline{{w^{\prime}}^2}}, \]
# Line 470  is solved numerically using an implicit Line 463  is solved numerically using an implicit
463  and is written:  and is written:
464    
465  \[  \[
466  {\dd{}{t} ({{\h} q^2})} - { \pp{}{z} ({ {5 \over 3} {{\lambda}_1} q { \pp {}{z}  {\dd{}{t} ({{\h} q^2})} - { \pp{}{z} ({ \frac{5}{3} {{\lambda}_1} q { \pp {}{z}
467  ({\h}q^2)} })} =  ({\h}q^2)} })} =
468  {- \overline{{u^{\prime}}{w^{\prime}}} { \pp{U}{z} }} - {\overline{{v^{\prime}}{w^{\prime}}}  {- \overline{{u^{\prime}}{w^{\prime}}} { \pp{U}{z} }} - {\overline{{v^{\prime}}{w^{\prime}}}
469  { \pp{V}{z} }} + {{g \over {\Theta_0}}{\overline{{w^{\prime}}{{{\theta}_v}^{\prime}}}} }  { \pp{V}{z} }} + {\frac{g}{\Theta_0}{\overline{{w^{\prime}}{{{\theta}_v}^{\prime}}}}
470  - { q^3 \over {{\Lambda} _1} }  - \frac{ q^3}{{\Lambda}_1} }
471  \]  \]
472    
473  where $q$ is the turbulent velocity, ${u^{\prime}}$, ${v^{\prime}}$, ${w^{\prime}}$ and  where $q$ is the turbulent velocity, ${u^{\prime}}$, ${v^{\prime}}$, ${w^{\prime}}$ and
# Line 492  of TKE. Line 485  of TKE.
485    
486  In the level 2.5 approach, the vertical fluxes of the scalars $\theta_v$ and $q$ and the  In the level 2.5 approach, the vertical fluxes of the scalars $\theta_v$ and $q$ and the
487  wind components $u$ and $v$ are expressed in terms of the diffusion coefficients $K_h$ and  wind components $u$ and $v$ are expressed in terms of the diffusion coefficients $K_h$ and
488  $K_m$, respectively.  In the statisically realizable level 2.5 turbulence scheme of Helfand  $K_m$, respectively.  In the statisically realizable level 2.5 turbulence scheme of
489  and Labraga (1988), these diffusion coefficients are expressed as  \cite{helflab:88}, these diffusion coefficients are expressed as
490    
491  \[  \[
492  K_h  K_h
493   = \left\{ \begin{array}{l@{\quad\mbox{for}\quad}l} q \, \ell \, S_H(G_M,G_H) \, & \mbox{decaying turbulence}   = \left\{ \begin{array}{l@{\quad\mbox{for}\quad}l} q \, \ell \, S_H(G_M,G_H) \, & \mbox{decaying turbulence}
494  \\ { q^2 \over {q_e} } \, \ell \, S_{H}(G_{M_e},G_{H_e}) \, & \mbox{growing turbulence} \end{array} \right.  \\ \frac{ q^2 }{ q_e } \, \ell \, S_{H}(G_{M_e},G_{H_e}) \, & \mbox{growing turbulence} \end{array} \right.
495  \]  \]
496    
497  and  and
# Line 506  and Line 499  and
499  \[  \[
500  K_m  K_m
501   = \left\{ \begin{array}{l@{\quad\mbox{for}\quad}l} q \, \ell \, S_M(G_M,G_H) \, & \mbox{decaying turbulence}                   = \left\{ \begin{array}{l@{\quad\mbox{for}\quad}l} q \, \ell \, S_M(G_M,G_H) \, & \mbox{decaying turbulence}                
502  \\ { q^2 \over {q_e} } \, \ell \, S_{M}(G_{M_e},G_{H_e}) \, & \mbox{growing turbulence} \end{array} \right.  \\ \frac{ q^2 }{ q_e } \, \ell \, S_{M}(G_{M_e},G_{H_e}) \, & \mbox{growing turbulence} \end{array} \right.
503  \]  \]
504    
505  where the subscript $e$ refers to the value under conditions of local equillibrium  where the subscript $e$ refers to the value under conditions of local equillibrium
# Line 518  Both $G_H$ and $G_M$, and their equilibr Line 511  Both $G_H$ and $G_M$, and their equilibr
511  are functions of the Richardson number:  are functions of the Richardson number:
512    
513  \[  \[
514  {\bf RI} = { { {g \over \theta_v} \pp {\theta_v}{z} } \over { (\pp{u}{z})^2 + (\pp{v}{z})^2 } }  {\bf RI} = \frac{ \frac{g}{\theta_v} \pp{\theta_v}{z} }{ (\pp{u}{z})^2 + (\pp{v}{z})^2 }
515   =  {  {c_p \pp{\theta_v}{z} \pp{P^ \kappa}{z} } \over { (\pp{u}{z})^2 + (\pp{v}{z})^2 } } .   =  \frac{c_p \pp{\theta_v}{z} \pp{P^ \kappa}{z} }{ (\pp{u}{z})^2 + (\pp{v}{z})^2 } .
516  \]  \]
517    
518  Negative values indicate unstable buoyancy and shear, small positive values ($<0.2$)  Negative values indicate unstable buoyancy and shear, small positive values ($<0.2$)
519  indicate dominantly unstable shear, and large positive values indicate dominantly stable  indicate dominantly unstable shear, and large positive values indicate dominantly stable
520  stratification.  stratification.
521    
522  Turbulent eddy diffusion coefficients of momentum, heat and moisture in the surface layer,  Turbulent eddy diffusion coefficients of momentum, heat and moisture in the
523  which corresponds to the lowest GCM level (see \ref{tab:fizhi:sigma}),  surface layer, which corresponds to the lowest GCM level
524    (see {\it --- missing table ---}%\ref{tab:fizhi:sigma}
525    ),
526  are calculated using stability-dependant functions based on Monin-Obukhov theory:  are calculated using stability-dependant functions based on Monin-Obukhov theory:
527  \[  \[
528  {K_m} (surface) = C_u \times u_* = C_D W_s  {K_m} (surface) = C_u \times u_* = C_D W_s
# Line 543  and $W_s$ is the magnitude of the surfac Line 538  and $W_s$ is the magnitude of the surfac
538  $C_u$ is the dimensionless exchange coefficient for momentum from the surface layer  $C_u$ is the dimensionless exchange coefficient for momentum from the surface layer
539  similarity functions:  similarity functions:
540  \[  \[
541  {C_u} = {u_* \over W_s} = { k \over \psi_{m} }  {C_u} = \frac{u_* }{ W_s} = \frac{ k }{ \psi_{m} }
542  \]  \]
543  where k is the Von Karman constant and $\psi_m$ is the surface layer non-dimensional  where k is the Von Karman constant and $\psi_m$ is the surface layer non-dimensional
544  wind shear given by  wind shear given by
545  \[  \[
546  \psi_{m} = {\int_{\zeta_{0}}^{\zeta} {\phi_{m} \over \zeta} d \zeta} .  \psi_{m} = {\int_{\zeta_{0}}^{\zeta} \frac{\phi_{m} }{ \zeta} d \zeta} .
547  \]  \]
548  Here $\zeta$ is the non-dimensional stability parameter, and  Here $\zeta$ is the non-dimensional stability parameter, and
549  $\phi_m$ is the similarity function of $\zeta$ which expresses the stability dependance of  $\phi_m$ is the similarity function of $\zeta$ which expresses the stability dependance of
# Line 558  layers. Line 553  layers.
553  $C_t$ is the dimensionless exchange coefficient for heat and  $C_t$ is the dimensionless exchange coefficient for heat and
554  moisture from the surface layer similarity functions:  moisture from the surface layer similarity functions:
555  \[  \[
556  {C_t} = -{( {\overline{w^{\prime}\theta^{\prime}}}) \over {u_* \Delta \theta }} =  {C_t} = -\frac{( \overline{w^{\prime}\theta^{\prime}}) }{ u_* \Delta \theta } =
557  -{( {\overline{w^{\prime}q^{\prime}}}) \over {u_* \Delta q }} =  -\frac{( \overline{w^{\prime}q^{\prime}}) }{ u_* \Delta q } =
558  { k \over { (\psi_{h} + \psi_{g}) } }  \frac{ k }{ (\psi_{h} + \psi_{g}) }
559  \]  \]
560  where $\psi_h$ is the surface layer non-dimensional temperature gradient given by  where $\psi_h$ is the surface layer non-dimensional temperature gradient given by
561  \[  \[
562  \psi_{h} = {\int_{\zeta_{0}}^{\zeta} {\phi_{h} \over \zeta} d \zeta} .  \psi_{h} = {\int_{\zeta_{0}}^{\zeta} \frac{\phi_{h} }{ \zeta} d \zeta} .
563  \]  \]
564  Here $\phi_h$ is the similarity function of $\zeta$, which expresses the stability dependance of  Here $\phi_h$ is the similarity function of $\zeta$, which expresses the stability dependance of
565  the temperature and moisture gradients, and is specified differently for stable and unstable  the temperature and moisture gradients, and is specified differently for stable and unstable
566  layers according to Helfand and Schubert, 1995.  layers according to \cite{helfschu:95}.
567    
568  $\psi_g$ is the non-dimensional temperature or moisture gradient in the viscous sublayer,  $\psi_g$ is the non-dimensional temperature or moisture gradient in the viscous sublayer,
569  which is the mosstly laminar region between the surface and the tops of the roughness  which is the mosstly laminar region between the surface and the tops of the roughness
570  elements, in which temperature and moisture gradients can be quite large.  elements, in which temperature and moisture gradients can be quite large.
571  Based on Yaglom and Kader (1974):  Based on \cite{yagkad:74}:
572  \[  \[
573  \psi_{g} = { 0.55 (Pr^{2/3} - 0.2) \over \nu^{1/2} }  \psi_{g} = \frac{ 0.55 (Pr^{2/3} - 0.2) }{ \nu^{1/2} }
574  (h_{0}u_{*} - h_{0_{ref}}u_{*_{ref}})^{1/2}  (h_{0}u_{*} - h_{0_{ref}}u_{*_{ref}})^{1/2}
575  \]  \]
576  where Pr is the Prandtl number for air, $\nu$ is the molecular viscosity, $z_{0}$ is the  where Pr is the Prandtl number for air, $\nu$ is the molecular viscosity, $z_{0}$ is the
# Line 584  $h_{0} = 30z_{0}$ with a maximum value o Line 579  $h_{0} = 30z_{0}$ with a maximum value o
579    
580  The surface roughness length over oceans is is a function of the surface-stress velocity,  The surface roughness length over oceans is is a function of the surface-stress velocity,
581  \[  \[
582  {z_0} = c_1u^3_* + c_2u^2_* + c_3u_* + c_4 + {c_5 \over {u_*}}  {z_0} = c_1u^3_* + c_2u^2_* + c_3u_* + c_4 + \frac{c_5 }{ u_*}
583  \]  \]
584  where the constants are chosen to interpolate between the reciprocal relation of  where the constants are chosen to interpolate between the reciprocal relation of
585  Kondo(1975) for weak winds, and the piecewise linear relation of Large and Pond(1981)  \cite{kondo:75} for weak winds, and the piecewise linear relation of \cite{larpond:81}
586  for moderate to large winds.  Roughness lengths over land are specified  for moderate to large winds.  Roughness lengths over land are specified
587  from the climatology of Dorman and Sellers (1989).  from the climatology of \cite{dorsell:89}.
588    
589  For an unstable surface layer, the stability functions, chosen to interpolate between the  For an unstable surface layer, the stability functions, chosen to interpolate between the
590  condition of small values of $\beta$ and the convective limit, are the KEYPS function  condition of small values of $\beta$ and the convective limit, are the KEYPS function
591  (Panofsky, 1973) for momentum, and its generalization for heat and moisture:    (\cite{pano:73}) for momentum, and its generalization for heat and moisture:  
592  \[  \[
593  {\phi_m}^4 - 18 \zeta {\phi_m}^3 = 1 \hspace{1cm} ; \hspace{1cm}  {\phi_m}^4 - 18 \zeta {\phi_m}^3 = 1 \hspace{1cm} ; \hspace{1cm}
594  {\phi_h}^2 - 18 \zeta {\phi_h}^3 = 1 \hspace{1cm} .  {\phi_h}^2 - 18 \zeta {\phi_h}^3 = 1 \hspace{1cm} .
# Line 602  The function for heat and moisture assur Line 597  The function for heat and moisture assur
597  speed approaches zero.  speed approaches zero.
598    
599  For a stable surface layer, the stability functions are the observationally  For a stable surface layer, the stability functions are the observationally
600  based functions of Clarke (1970),  slightly modified for  based functions of \cite{clarke:70},  slightly modified for
601  the momemtum flux:    the momemtum flux:  
602  \[  \[
603  {\phi_m} = { { 1 + 5 {{\zeta}_1} } \over { 1 + 0.00794 {{\zeta}_1}  {\phi_m} = \frac{ 1 + 5 {{\zeta}_1} }{ 1 + 0.00794 {\zeta}_1
604  (1+ 5 {{\zeta}_1}) } } \hspace{1cm} ; \hspace{1cm}  (1+ 5 {\zeta}_1) } \hspace{1cm} ; \hspace{1cm}
605  {\phi_h} = { { 1 + 5 {{\zeta}_1} } \over { 1 + 0.00794 {\zeta}  {\phi_h} = \frac{ 1 + 5 {{\zeta}_1} }{ 1 + 0.00794 {\zeta}
606  (1+ 5 {{\zeta}_1}) } } .  (1+ 5 {{\zeta}_1}) } .
607  \]  \]
608  The moisture flux also depends on a specified evapotranspiration  The moisture flux also depends on a specified evapotranspiration
609  coefficient, set to unity over oceans and dependant on the climatological ground wetness over  coefficient, set to unity over oceans and dependant on the climatological ground wetness over
# Line 653  humidity of the surface and of the lowes Line 648  humidity of the surface and of the lowes
648    
649  The heat conduction through sea ice, $Q_{ice}$, is given by  The heat conduction through sea ice, $Q_{ice}$, is given by
650  \[  \[
651  {Q_{ice}} = {C_{ti} \over {H_i}} (T_i-T_g)  {Q_{ice}} = \frac{C_{ti} }{ H_i} (T_i-T_g)
652  \]  \]
653  where $C_{ti}$ is the thermal conductivity of ice, $H_i$ is the ice thickness, assumed to  where $C_{ti}$ is the thermal conductivity of ice, $H_i$ is the ice thickness, assumed to
654  be $3 \hspace{.1cm} m$ where sea ice is present, $T_i$ is 273 degrees Kelvin, and $T_g$ is the  be $3 \hspace{.1cm} m$ where sea ice is present, $T_i$ is 273 degrees Kelvin, and $T_g$ is the
655  surface temperature of the ice.  surface temperature of the ice.
656    
657  $C_g$ is the total heat capacity of the ground, obtained by solving a heat diffusion equation  $C_g$ is the total heat capacity of the ground, obtained by solving a heat diffusion equation
658  for the penetration of the diurnal cycle into the ground (Blackadar, 1977), and is given by:  for the penetration of the diurnal cycle into the ground (\cite{black:77}), and is given by:
659  \[  \[
660  C_g = \sqrt{ {\lambda C_s \over 2\omega} } = \sqrt{(0.386 + 0.536W + 0.15W^2)2\times10^{-3}  C_g = \sqrt{ \frac{\lambda C_s }{ 2\omega} } = \sqrt{(0.386 + 0.536W + 0.15W^2)2\times10^{-3}
661  {86400 \over 2 \pi} } \, \, .  \frac{86400}{2\pi} } \, \, .
662  \]  \]
663  Here, the thermal conductivity, $\lambda$, is equal to $2\times10^{-3}$ ${ly\over{ sec}}  Here, the thermal conductivity, $\lambda$, is equal to $2\times10^{-3}$ $\frac{ly}{sec}
664  {cm \over {^oK}}$,      \frac{cm}{K}$,
665  the angular velocity of the earth, $\omega$, is written as $86400$ $sec/day$ divided  the angular velocity of the earth, $\omega$, is written as $86400$ $sec/day$ divided
666  by $2 \pi$ $radians/    by $2 \pi$ $radians/  
667  day$, and the expression for $C_s$, the heat capacity per unit volume at the surface,  day$, and the expression for $C_s$, the heat capacity per unit volume at the surface,
668  is a function of the ground wetness, $W$.  is a function of the ground wetness, $W$.
669    
670  \subsubsection{Land Surface Processes}  Land Surface Processes:
671    
672  \paragraph{Surface Type}  \paragraph{Surface Type}
673  The fizhi package surface Types are designated using the Koster-Suarez (1992) mosaic  The fizhi package surface Types are designated using the Koster-Suarez (\cite{ks:91,ks:92})
674  philosophy which allows multiple ``tiles'', or multiple surface types, in any one  Land Surface Model (LSM) mosaic philosophy which allows multiple ``tiles'', or multiple surface
675  grid cell. The Koster-Suarez Land Surface Model (LSM) surface type classifications  types, in any one grid cell. The Koster-Suarez LSM surface type classifications
676  are shown in Table \ref{tab:fizhi:surftype}. The surface types and the percent of the grid  are shown in Table \ref{tab:fizhi:surftype}. The surface types and the percent of the grid
677  cell occupied by any surface type were derived from the surface classification of  cell occupied by any surface type were derived from the surface classification of
678  Defries and Townshend (1994), and information about the location of permanent  \cite{deftow:94}, and information about the location of permanent
679  ice was obtained from the classifications of Dorman and Sellers (1989).  ice was obtained from the classifications of \cite{dorsell:89}.
680  The surface type for the \txt GCM grid is shown in Figure \ref{fig:fizhi:surftype}.  The surface type map for a $1^\circ$ grid is shown in Figure \ref{fig:fizhi:surftype}.
681  The determination of the land or sea category of surface type was made from NCAR's  The determination of the land or sea category of surface type was made from NCAR's
682  10 minute by 10 minute Navy topography  10 minute by 10 minute Navy topography
683  dataset, which includes information about the percentage of water-cover at any point.  dataset, which includes information about the percentage of water-cover at any point.
684  The data were averaged to the model's \fxf and \txt grid resolutions,  The data were averaged to the model's grid resolutions,
685  and any grid-box whose averaged water percentage was $\geq 60 \%$ was  and any grid-box whose averaged water percentage was $\geq 60 \%$ was
686  defined as a water point. The \fxf grid Land-Water designation was further modified  defined as a water point. The Land-Water designation was further modified
687  subjectively to ensure sufficient representation from small but isolated land and water regions.  subjectively to ensure sufficient representation from small but isolated land and water regions.
688    
689  \begin{table}  \begin{table}
# Line 712  Type & Vegetation Designation \\ \hline Line 707  Type & Vegetation Designation \\ \hline
707  100 & Ocean \\ \hline  100 & Ocean \\ \hline
708  \end{tabular}  \end{tabular}
709  \end{center}  \end{center}
710  \caption{Surface type designations used to compute surface roughness (over land)  \caption{Surface type designations.}
 and surface albedo.}  
711  \label{tab:fizhi:surftype}  \label{tab:fizhi:surftype}
712  \end{table}  \end{table}
713    
   
714  \begin{figure*}[htbp]  \begin{figure*}[htbp]
715    \centerline{  \epsfysize=7in  \epsfbox{part6/surftypes.ps}}    \centerline{  \epsfysize=4.0in  \epsfbox{s_phys_pkgs/figs/surftype.eps}}
716    \vspace{0.3in}    \vspace{0.2in}
717    \caption  {Surface Type Compinations at \txt resolution.}    \caption  {Surface Type Combinations.}
718    \label{fig:fizhi:surftype}    \label{fig:fizhi:surftype}
719  \end{figure*}  \end{figure*}
720    
721  \begin{figure*}[htbp]  % \rotatebox{270}{\centerline{  \epsfysize=4in  \epsfbox{s_phys_pkgs/figs/surftypes.eps}}}
722    \centerline{  \epsfysize=7in  \epsfbox{part6/surftypes.descrip.ps}}  % \rotatebox{270}{\centerline{  \epsfysize=4in  \epsfbox{s_phys_pkgs/figs/surftypes.descrip.eps}}}
723    \vspace{0.3in}  %\begin{figure*}[htbp]
724    \caption  {Surface Type Descriptions.}  %  \centerline{  \epsfysize=4in  \epsfbox{s_phys_pkgs/figs/surftypes.descrip.ps}}
725    \label{fig:fizhi:surftype.desc}  %  \vspace{0.3in}
726  \end{figure*}  %  \caption  {Surface Type Descriptions.}
727    %  \label{fig:fizhi:surftype.desc}
728    %\end{figure*}
729    
730    
731  \paragraph{Surface Roughness}  \paragraph{Surface Roughness}
732  The surface roughness length over oceans is computed iteratively with the wind  The surface roughness length over oceans is computed iteratively with the wind
733  stress by the surface layer parameterization (Helfand and Schubert, 1991).  stress by the surface layer parameterization (\cite{helfschu:95}).
734  It employs an interpolation between the functions of Large and Pond (1981)  It employs an interpolation between the functions of \cite{larpond:81}
735  for high winds and of Kondo (1975) for weak winds.  for high winds and of \cite{kondo:75} for weak winds.
736    
737    
738  \paragraph{Albedo}  \paragraph{Albedo}
739  The surface albedo computation, described in Koster and Suarez (1991),  The surface albedo computation, described in \cite{ks:91},
740  employs the ``two stream'' approximation used in Sellers' (1987) Simple Biosphere (SiB)  employs the ``two stream'' approximation used in Sellers' (1987) Simple Biosphere (SiB)
741  Model which distinguishes between the direct and diffuse albedos in the visible  Model which distinguishes between the direct and diffuse albedos in the visible
742  and in the near infra-red spectral ranges. The albedos are functions of the observed  and in the near infra-red spectral ranges. The albedos are functions of the observed
# Line 750  sun), the greenness fraction, the vegeta Line 745  sun), the greenness fraction, the vegeta
745  Modifications are made to account for the presence of snow, and its depth relative  Modifications are made to account for the presence of snow, and its depth relative
746  to the height of the vegetation elements.  to the height of the vegetation elements.
747    
748  \subsubsection{Gravity Wave Drag}  \paragraph{Gravity Wave Drag}
749  The fizhi package employs the gravity wave drag scheme of Zhou et al. (1996).  
750    The fizhi package employs the gravity wave drag scheme of \cite{zhouetal:95}).
751  This scheme is a modified version of Vernekar et al. (1992),  This scheme is a modified version of Vernekar et al. (1992),
752  which was based on Alpert et al. (1988) and Helfand et al. (1987).    which was based on Alpert et al. (1988) and Helfand et al. (1987).  
753  In this version, the gravity wave stress at the surface is  In this version, the gravity wave stress at the surface is
754  based on that derived by Pierrehumbert (1986) and is given by:  based on that derived by Pierrehumbert (1986) and is given by:
755    
756  \bq  \bq
757  |\vec{\tau}_{sfc}| = {\rho U^3\over{N \ell^*}} \left(F_r^2 \over{1+F_r^2}\right) \, \, ,  |\vec{\tau}_{sfc}| = \frac{\rho U^3}{N \ell^*} \left( \frac{F_r^2}{1+F_r^2}\right) \, \, ,
758  \eq  \eq
759    
760  where $F_r = N h /U$ is the Froude number, $N$ is the {\em Brunt - V\"{a}is\"{a}l\"{a}} frequency, $U$ is the  where $F_r = N h /U$ is the Froude number, $N$ is the {\em Brunt - V\"{a}is\"{a}l\"{a}} frequency, $U$ is the
# Line 768  A modification introduced by Zhou et al. Line 764  A modification introduced by Zhou et al.
764  escape through the top of the model, although this effect is small for the current 70-level model.    escape through the top of the model, although this effect is small for the current 70-level model.  
765  The subgrid scale standard deviation is defined by $h$, and is not allowed to exceed 400 m.  The subgrid scale standard deviation is defined by $h$, and is not allowed to exceed 400 m.
766    
767  The effects of using this scheme within a GCM are shown in Takacs and Suarez (1996).  The effects of using this scheme within a GCM are shown in \cite{taksz:96}.
768  Experiments using the gravity wave drag parameterization yielded significant and  Experiments using the gravity wave drag parameterization yielded significant and
769  beneficial impacts on both the time-mean flow and the transient statistics of the  beneficial impacts on both the time-mean flow and the transient statistics of the
770  a GCM climatology, and have eliminated most of the worst dynamically driven biases  a GCM climatology, and have eliminated most of the worst dynamically driven biases
# Line 784  of mountain torque (through a redistribu Line 780  of mountain torque (through a redistribu
780  convergence (through a reduction in the flux of westerly momentum by transient flow eddies).    convergence (through a reduction in the flux of westerly momentum by transient flow eddies).  
781    
782    
783  \subsubsection{Boundary Conditions and other Input Data}  Boundary Conditions and other Input Data:
784    
785  Required fields which are not explicitly predicted or diagnosed during model execution must  Required fields which are not explicitly predicted or diagnosed during model execution must
786  either be prescribed internally or obtained from external data sets.  In the fizhi package these  either be prescribed internally or obtained from external data sets.  In the fizhi package these
# Line 792  fields include:  sea surface temperature Line 788  fields include:  sea surface temperature
788  vegetation index, and the radiation-related background levels of: ozone, carbon dioxide,  vegetation index, and the radiation-related background levels of: ozone, carbon dioxide,
789  and stratospheric moisture.  and stratospheric moisture.
790    
791  Boundary condition data sets are available at the model's \fxf and \txt  Boundary condition data sets are available at the model's
792  resolutions for either climatological or yearly varying conditions.  resolutions for either climatological or yearly varying conditions.
793  Any frequency of boundary condition data can be used in the fizhi package;  Any frequency of boundary condition data can be used in the fizhi package;
794  however, the current selection of data is summarized in Table \ref{tab:fizhi:bcdata}\@.  however, the current selection of data is summarized in Table \ref{tab:fizhi:bcdata}\@.
795  The time mean values are interpolated during each model timestep to the  The time mean values are interpolated during each model timestep to the
796  current time. Future model versions will incorporate boundary conditions at  current time.
 higher spatial \mbox{($1^\circ$ x $1^\circ$)} resolutions.  
797    
798  \begin{table}[htb]  \begin{table}[htb]
799  \begin{center}  \begin{center}
# Line 825  current years and frequencies available. Line 820  current years and frequencies available.
820  Surface geopotential heights are provided from an averaging of the Navy 10 minute  Surface geopotential heights are provided from an averaging of the Navy 10 minute
821  by 10 minute dataset supplied by the National Center for Atmospheric Research (NCAR) to the  by 10 minute dataset supplied by the National Center for Atmospheric Research (NCAR) to the
822  model's grid resolution. The original topography is first rotated to the proper grid-orientation  model's grid resolution. The original topography is first rotated to the proper grid-orientation
823  which is being run, and then    which is being run, and then  averages the data to the model resolution.  
 averages the data to the model resolution.    
 The averaged topography is then passed through a Lanczos (1966) filter in both dimensions  
 which removes the smallest  
 scales while inhibiting Gibbs phenomena.    
   
 In one dimension, we may define a cyclic function in $x$ as:  
 \begin{equation}  
 f(x) = {a_0 \over 2} + \sum_{k=1}^N \left( a_k \cos(kx) + b_k \sin(kx) \right)  
 \label{eq:fizhi:filt}  
 \end{equation}  
 where $N = { {\rm IM} \over 2 }$ and ${\rm IM}$ is the total number of points in the $x$ direction.  
 Defining $\Delta x = { 2 \pi \over {\rm IM}}$, we may define the average of $f(x)$ over a  
 $2 \Delta x$ region as:  
   
 \begin{equation}  
 \overline {f(x)} = {1 \over {2 \Delta x}} \int_{x-\Delta x}^{x+\Delta x} f(x^{\prime}) dx^{\prime}  
 \label{eq:fizhi:fave1}  
 \end{equation}  
   
 Using equation (\ref{eq:fizhi:filt}) in equation (\ref{eq:fizhi:fave1}) and integrating, we may write:  
   
 \begin{equation}  
 \overline {f(x)} = {a_0 \over 2} + {1 \over {2 \Delta x}}  
 \sum_{k=1}^N \left [  
 \left. a_k { \sin(kx^{\prime}) \over k } \right /_{x-\Delta x}^{x+\Delta x} -  
 \left. b_k { \cos(kx^{\prime}) \over k } \right /_{x-\Delta x}^{x+\Delta x}  
 \right]  
 \end{equation}  
 or  
   
 \begin{equation}  
 \overline {f(x)} = {a_0 \over 2} + \sum_{k=1}^N {\sin(k \Delta x) \over {k \Delta x}}  
 \left( a_k \cos(kx) + b_k \sin(kx) \right)  
 \label{eq:fizhi:fave2}  
 \end{equation}  
   
 Thus, the Fourier wave amplitudes are simply modified by the Lanczos filter response  
 function ${\sin(k\Delta x) \over {k \Delta x}}$.  This may be compared with an $mth$-order  
 Shapiro (1970) filter response function, defined as $1-\sin^m({k \Delta x \over 2})$,  
 shown in Figure \ref{fig:fizhi:lanczos}.  
 It should be noted that negative values in the topography resulting from  
 the filtering procedure are {\em not} filled.  
   
 \begin{figure*}[htbp]  
   \centerline{  \epsfysize=7.0in  \epsfbox{part6/lanczos.ps}}  
   \caption{ \label{fig:fizhi:lanczos} Comparison between the Lanczos and $mth$-order Shapiro filter  
   response functions for $m$ = 2, 4, and 8. }  
 \end{figure*}  
824    
825  The standard deviation of the subgrid-scale topography  The standard deviation of the subgrid-scale topography is computed by interpolating the 10 minute
826  is computed from a modified version of the the Navy 10 minute by 10 minute dataset.  data to the model's resolution and re-interpolating back to the 10 minute by 10 minute resolution.
 The 10 minute by 10 minute topography is passed through a wavelet  
 filter in both dimensions which removes the scale smaller than 20 minutes.  
 The topography is then averaged to $1^\circ x 1^\circ$ grid resolution, and then  
 re-interpolated back to the 10 minute by 10 minute resolution.  
827  The sub-grid scale variance is constructed based on this smoothed dataset.  The sub-grid scale variance is constructed based on this smoothed dataset.
828    
829    
830  \paragraph{Upper Level Moisture}  \paragraph{Upper Level Moisture}
831  The fizhi package uses climatological water vapor data above 100 mb from the Stratospheric Aerosol and Gas  The fizhi package uses climatological water vapor data above 100 mb from the Stratospheric Aerosol and Gas
832  Experiment (SAGE) as input into the model's radiation packages.  The SAGE data is archived  Experiment (SAGE) as input into the model's radiation packages.  The SAGE data is archived
833  as monthly zonal means at 5$^\circ$ latitudinal resolution.  The data is interpolated to the  as monthly zonal means at $5^\circ$ latitudinal resolution.  The data is interpolated to the
834  model's grid location and current time, and blended with the GCM's moisture data.  Below 300 mb,  model's grid location and current time, and blended with the GCM's moisture data.  Below 300 mb,
835  the model's moisture data is used.  Above 100 mb, the SAGE data is used.  Between 100 and 300 mb,  the model's moisture data is used.  Above 100 mb, the SAGE data is used.  Between 100 and 300 mb,
836  a linear interpolation (in pressure) is performed using the data from SAGE and the GCM.  a linear interpolation (in pressure) is performed using the data from SAGE and the GCM.
837    
838    
839  \subsection{Fizhi Diagnostics}  \subsubsection{Fizhi Diagnostics}
840    
841  \subsubsection{Fizhi Diagnostic Menu}  Fizhi Diagnostic Menu:
842  \label{sec:fizhi-diagnostics:menu}  \label{sec:pkg:fizhi:diagnostics}
843    
844  \begin{tabular}{llll}  \begin{tabular}{llll}
845  \hline\hline  \hline\hline
# Line 1424  a linear interpolation (in pressure) is Line 1367  a linear interpolation (in pressure) is
1367    
1368  \newpage  \newpage
1369    
1370  \subsubsection{Fizhi Diagnostic Description}  Fizhi Diagnostic Description:
1371    
1372  In this section we list and describe the diagnostic quantities available within the  In this section we list and describe the diagnostic quantities available within the
1373  GCM.  The diagnostics are listed in the order that they appear in the  GCM.  The diagnostics are listed in the order that they appear in the
1374  Diagnostic Menu, Section \ref{sec:fizhi-diagnostics:menu}.  Diagnostic Menu, Section \ref{sec:pkg:fizhi:diagnostics}.
1375  In all cases, each diagnostic as currently archived on the output datasets  In all cases, each diagnostic as currently archived on the output datasets
1376  is time-averaged over its diagnostic output frequency:  is time-averaged over its diagnostic output frequency:
1377    
1378  \[  \[
1379  {\bf DIAGNOSTIC} = {1 \over TTOT} \sum_{t=1}^{t=TTOT} diag(t)  {\bf DIAGNOSTIC} = \frac{1}{TTOT} \sum_{t=1}^{t=TTOT} diag(t)
1380  \]  \]
1381  where $TTOT = {{\bf NQDIAG} \over \Delta t}$, {\bf NQDIAG} is the  where $TTOT = \frac{ {\bf NQDIAG} }{\Delta t}$, {\bf NQDIAG} is the
1382  output frequency of the diagnostic, and $\Delta t$ is  output frequency of the diagnostic, and $\Delta t$ is
1383  the timestep over which the diagnostic is updated.    the timestep over which the diagnostic is updated.  
1384    
# Line 1507  conduction from the relatively warm ocea Line 1450  conduction from the relatively warm ocea
1450  through sea ice represents an additional energy source term for the ground temperature equation.  through sea ice represents an additional energy source term for the ground temperature equation.
1451    
1452  \[  \[
1453  {\bf QICE} = {C_{ti} \over {H_i}} (T_i-T_g)  {\bf QICE} = \frac{C_{ti}}{H_i} (T_i-T_g)
1454  \]  \]
1455    
1456  where $C_{ti}$ is the thermal conductivity of ice, $H_i$ is the ice thickness, assumed to  where $C_{ti}$ is the thermal conductivity of ice, $H_i$ is the ice thickness, assumed to
# Line 1549  the downward Shortwave flux and $F_{SW}^ Line 1492  the downward Shortwave flux and $F_{SW}^
1492  \noindent  \noindent
1493  The non-dimensional stability indicator is the ratio of the buoyancy to the shear:  The non-dimensional stability indicator is the ratio of the buoyancy to the shear:
1494  \[  \[
1495  {\bf RI} = { { {g \over \theta_v} \pp {\theta_v}{z} } \over { (\pp{u}{z})^2 + (\pp{v}{z})^2 } }  {\bf RI} = \frac{ \frac{g}{\theta_v} \pp {\theta_v}{z} }{ (\pp{u}{z})^2 + (\pp{v}{z})^2 }
1496   =  {  {c_p \pp{\theta_v}{z} \pp{P^ \kappa}{z} } \over { (\pp{u}{z})^2 + (\pp{v}{z})^2 } }   =  \frac{c_p \pp{\theta_v}{z} \pp{P^ \kappa}{z} }{ (\pp{u}{z})^2 + (\pp{v}{z})^2 }
1497  \]  \]
1498  \\  \\
1499  where we used the hydrostatic equation:  where we used the hydrostatic equation:
# Line 1569  stratification. Line 1512  stratification.
1512  The surface exchange coefficient is obtained from the similarity functions for the stability  The surface exchange coefficient is obtained from the similarity functions for the stability
1513   dependant flux profile relationships:   dependant flux profile relationships:
1514  \[  \[
1515  {\bf CT} = -{( {\overline{w^{\prime}\theta^{\prime}}}) \over {u_* \Delta \theta }} =  {\bf CT} = -\frac{( \overline{w^{\prime}\theta^{\prime}} ) }{ u_* \Delta \theta } =
1516  -{( {\overline{w^{\prime}q^{\prime}}}) \over {u_* \Delta q }} =  -\frac{( \overline{w^{\prime}q^{\prime}} ) }{ u_* \Delta q } =
1517  { k \over { (\psi_{h} + \psi_{g}) } }  \frac{ k }{ (\psi_{h} + \psi_{g}) }
1518  \]  \]
1519  where $\psi_h$ is the surface layer non-dimensional temperature change and $\psi_g$ is the  where $\psi_h$ is the surface layer non-dimensional temperature change and $\psi_g$ is the
1520  viscous sublayer non-dimensional temperature or moisture change:  viscous sublayer non-dimensional temperature or moisture change:
1521  \[  \[
1522  \psi_{h} = {\int_{\zeta_{0}}^{\zeta} {\phi_{h} \over \zeta} d \zeta} \hspace{1cm} and  \psi_{h} = \int_{\zeta_{0}}^{\zeta} \frac{\phi_{h} }{ \zeta} d \zeta \hspace{1cm} and
1523  \hspace{1cm} \psi_{g} = { 0.55 (Pr^{2/3} - 0.2) \over \nu^{1/2} }  \hspace{1cm} \psi_{g} = \frac{ 0.55 (Pr^{2/3} - 0.2) }{ \nu^{1/2} }
1524  (h_{0}u_{*} - h_{0_{ref}}u_{*_{ref}})^{1/2}  (h_{0}u_{*} - h_{0_{ref}}u_{*_{ref}})^{1/2}
1525  \]  \]
1526  and:  and:
# Line 1586  $h_{0} = 30z_{0}$ with a maximum value o Line 1529  $h_{0} = 30z_{0}$ with a maximum value o
1529  \noindent  \noindent
1530  $\phi_h$ is the similarity function of $\zeta$, which expresses the stability dependance of  $\phi_h$ is the similarity function of $\zeta$, which expresses the stability dependance of
1531  the temperature and moisture gradients, specified differently for stable and unstable  the temperature and moisture gradients, specified differently for stable and unstable
1532  layers according to Helfand and Schubert, 1993. k is the Von Karman constant, $\zeta$ is the  layers according to \cite{helfschu:95}. k is the Von Karman constant, $\zeta$ is the
1533  non-dimensional stability parameter, Pr is the Prandtl number for air, $\nu$ is the molecular  non-dimensional stability parameter, Pr is the Prandtl number for air, $\nu$ is the molecular
1534  viscosity, $z_{0}$ is the surface roughness length, $u_*$ is the surface stress velocity  viscosity, $z_{0}$ is the surface roughness length, $u_*$ is the surface stress velocity
1535  (see diagnostic number 67), and the subscript ref refers to a reference value.  (see diagnostic number 67), and the subscript ref refers to a reference value.
# Line 1599  viscosity, $z_{0}$ is the surface roughn Line 1542  viscosity, $z_{0}$ is the surface roughn
1542  The surface exchange coefficient is obtained from the similarity functions for the stability  The surface exchange coefficient is obtained from the similarity functions for the stability
1543   dependant flux profile relationships:   dependant flux profile relationships:
1544  \[  \[
1545  {\bf CU} = {u_* \over W_s} = { k \over \psi_{m} }  {\bf CU} = \frac{u_* }{ W_s} = \frac{ k }{ \psi_{m} }
1546  \]  \]
1547  where $\psi_m$ is the surface layer non-dimensional wind shear:  where $\psi_m$ is the surface layer non-dimensional wind shear:
1548  \[  \[
1549  \psi_{m} = {\int_{\zeta_{0}}^{\zeta} {\phi_{m} \over \zeta} d \zeta}  \psi_{m} = {\int_{\zeta_{0}}^{\zeta} \frac{\phi_{m} }{ \zeta} d \zeta}
1550  \]  \]
1551  \noindent  \noindent
1552  $\phi_m$ is the similarity function of $\zeta$, which expresses the stability dependance of  $\phi_m$ is the similarity function of $\zeta$, which expresses the stability dependance of
1553  the temperature and moisture gradients, specified differently for stable and unstable layers  the temperature and moisture gradients, specified differently for stable and unstable layers
1554  according to Helfand and Schubert, 1993. k is the Von Karman constant, $\zeta$ is the  according to \cite{helfschu:95}. k is the Von Karman constant, $\zeta$ is the
1555  non-dimensional stability parameter, $u_*$ is the surface stress velocity  non-dimensional stability parameter, $u_*$ is the surface stress velocity
1556  (see diagnostic number 67), and $W_s$ is the magnitude of the surface layer wind.  (see diagnostic number 67), and $W_s$ is the magnitude of the surface layer wind.
1557  \\  \\
# Line 1620  non-dimensional stability parameter, $u_ Line 1563  non-dimensional stability parameter, $u_
1563  In the level 2.5 version of the Mellor-Yamada (1974) hierarchy, the turbulent heat or  In the level 2.5 version of the Mellor-Yamada (1974) hierarchy, the turbulent heat or
1564  moisture flux for the atmosphere above the surface layer can be expressed as a turbulent  moisture flux for the atmosphere above the surface layer can be expressed as a turbulent
1565  diffusion coefficient $K_h$ times the negative of the gradient of potential temperature  diffusion coefficient $K_h$ times the negative of the gradient of potential temperature
1566  or moisture. In the Helfand and Labraga (1988) adaptation of this closure, $K_h$  or moisture. In the \cite{helflab:88} adaptation of this closure, $K_h$
1567  takes the form:  takes the form:
1568  \[  \[
1569  {\bf ET} = K_h = -{( {\overline{w^{\prime}\theta_v^{\prime}}}) \over {\pp{\theta_v}{z}} }  {\bf ET} = K_h = -\frac{( \overline{w^{\prime}\theta_v^{\prime}}) }{ \pp{\theta_v}{z} }
1570   = \left\{ \begin{array}{l@{\quad\mbox{for}\quad}l} q \, \ell \, S_H(G_M,G_H) & \mbox{decaying turbulence}   = \left\{ \begin{array}{l@{\quad\mbox{for}\quad}l} q \, \ell \, S_H(G_M,G_H) & \mbox{decaying turbulence}
1571  \\ { q^2 \over {q_e} } \, \ell \, S_{H}(G_{M_e},G_{H_e}) & \mbox{growing turbulence} \end{array} \right.  \\ \frac{ q^2 }{ q_e } \, \ell \, S_{H}(G_{M_e},G_{H_e}) & \mbox{growing turbulence} \end{array} \right.
1572  \]  \]
1573  where $q$ is the turbulent velocity, or $\sqrt{2*turbulent \hspace{.2cm} kinetic \hspace{.2cm}  where $q$ is the turbulent velocity, or $\sqrt{2*turbulent \hspace{.2cm} kinetic \hspace{.2cm}
1574  energy}$, $q_e$ is the turbulence velocity derived from the more simple level 2.0 model,  energy}$, $q_e$ is the turbulence velocity derived from the more simple level 2.0 model,
# Line 1639  are functions of the Richardson number. Line 1582  are functions of the Richardson number.
1582    
1583  \noindent  \noindent
1584  For the detailed equations and derivations of the modified level 2.5 closure scheme,  For the detailed equations and derivations of the modified level 2.5 closure scheme,
1585  see Helfand and Labraga, 1988.  see \cite{helflab:88}.
1586    
1587  \noindent  \noindent
1588  In the surface layer, ${\bf {ET}}$ is the exchange coefficient for heat and moisture,  In the surface layer, ${\bf {ET}}$ is the exchange coefficient for heat and moisture,
# Line 1661  and $W_s$ is the magnitude of the surfac Line 1604  and $W_s$ is the magnitude of the surfac
1604  In the level 2.5 version of the Mellor-Yamada (1974) hierarchy, the turbulent heat  In the level 2.5 version of the Mellor-Yamada (1974) hierarchy, the turbulent heat
1605  momentum flux for the atmosphere above the surface layer can be expressed as a turbulent  momentum flux for the atmosphere above the surface layer can be expressed as a turbulent
1606  diffusion coefficient $K_m$ times the negative of the gradient of the u-wind.  diffusion coefficient $K_m$ times the negative of the gradient of the u-wind.
1607  In the Helfand and Labraga (1988) adaptation of this closure, $K_m$  In the \cite{helflab:88} adaptation of this closure, $K_m$
1608  takes the form:  takes the form:
1609  \[  \[
1610  {\bf EU} = K_m = -{( {\overline{u^{\prime}w^{\prime}}}) \over {\pp{U}{z}} }  {\bf EU} = K_m = -\frac{( \overline{u^{\prime}w^{\prime}} ) }{ \pp{U}{z} }
1611   = \left\{ \begin{array}{l@{\quad\mbox{for}\quad}l} q \, \ell \, S_M(G_M,G_H) & \mbox{decaying turbulence}   = \left\{ \begin{array}{l@{\quad\mbox{for}\quad}l} q \, \ell \, S_M(G_M,G_H) & \mbox{decaying turbulence}
1612  \\ { q^2 \over {q_e} } \, \ell \, S_{M}(G_{M_e},G_{H_e}) & \mbox{growing turbulence} \end{array} \right.  \\ \frac{ q^2 }{ q_e } \, \ell \, S_{M}(G_{M_e},G_{H_e}) & \mbox{growing turbulence} \end{array} \right.
1613  \]  \]
1614  \noindent  \noindent
1615  where $q$ is the turbulent velocity, or $\sqrt{2*turbulent \hspace{.2cm} kinetic \hspace{.2cm}  where $q$ is the turbulent velocity, or $\sqrt{2*turbulent \hspace{.2cm} kinetic \hspace{.2cm}
# Line 1681  are functions of the Richardson number. Line 1624  are functions of the Richardson number.
1624    
1625  \noindent  \noindent
1626  For the detailed equations and derivations of the modified level 2.5 closure scheme,  For the detailed equations and derivations of the modified level 2.5 closure scheme,
1627  see Helfand and Labraga, 1988.  see \cite{helflab:88}.
1628    
1629  \noindent  \noindent
1630  In the surface layer, ${\bf {EU}}$ is the exchange coefficient for momentum,  In the surface layer, ${\bf {EU}}$ is the exchange coefficient for momentum,
# Line 1769  equation. Line 1712  equation.
1712  \]  \]
1713  where:  where:
1714  \[  \[
1715  \left.{\pp{T}{t}}\right|_{c} = R \sum_i \left( \alpha { m_B \over c_p} \Gamma_s \right)_i  \left.{\pp{T}{t}}\right|_{c} = R \sum_i \left( \alpha \frac{m_B}{c_p} \Gamma_s \right)_i
1716  \hspace{.4cm} and  \hspace{.4cm} and
1717  \hspace{.4cm} \left.{\pp{T}{t}}\right|_{ls} = {L \over c_p } (q^*-q)  \hspace{.4cm} \left.{\pp{T}{t}}\right|_{ls} = \frac{L}{c_p} (q^*-q)
1718  \]  \]
1719  and  and
1720  \[  \[
# Line 1799  $R$ is the rain re-evaporation adjustmen Line 1742  $R$ is the rain re-evaporation adjustmen
1742  \]  \]
1743  where:  where:
1744  \[  \[
1745  \left.{\pp{q}{t}}\right|_{c} = R \sum_i \left( \alpha { m_B \over {L}}(\Gamma_h-\Gamma_s) \right)_i  \left.{\pp{q}{t}}\right|_{c} = R \sum_i \left( \alpha \frac{m_B}{L}(\Gamma_h-\Gamma_s) \right)_i
1746  \hspace{.4cm} and  \hspace{.4cm} and
1747  \hspace{.4cm} \left.{\pp{q}{t}}\right|_{ls} = (q^*-q)  \hspace{.4cm} \left.{\pp{q}{t}}\right|_{ls} = (q^*-q)
1748  \]  \]
# Line 1845  F_{LW} = C(p,p') \cdot F^{clearsky}_{LW} Line 1788  F_{LW} = C(p,p') \cdot F^{clearsky}_{LW}
1788  Finally, the net longwave heating rate is calculated as the vertical divergence of the  Finally, the net longwave heating rate is calculated as the vertical divergence of the
1789  net terrestrial radiative fluxes:  net terrestrial radiative fluxes:
1790  \[  \[
1791  \pp{\rho c_p T}{t} = - {\partial \over \partial z} F_{LW}^{NET} ,  \pp{\rho c_p T}{t} = - \p{z} F_{LW}^{NET} ,
1792  \]  \]
1793  or  or
1794  \[  \[
1795  {\bf RADLW} = \frac{g}{c_p \pi} {\partial \over \partial \sigma} F_{LW}^{NET} .  {\bf RADLW} = \frac{g}{c_p \pi} \p{\sigma} F_{LW}^{NET} .
1796  \]  \]
1797    
1798  \noindent  \noindent
# Line 1880  input at the top of the atmosphere. Line 1823  input at the top of the atmosphere.
1823  \noindent  \noindent
1824  The heating rate due to Shortwave Radiation under cloudy skies is defined as:  The heating rate due to Shortwave Radiation under cloudy skies is defined as:
1825  \[  \[
1826  \pp{\rho c_p T}{t} = - {\partial \over \partial z} F(cloudy)_{SW}^{NET} \cdot {\rm RADSWT},  \pp{\rho c_p T}{t} = - \p{z} F(cloudy)_{SW}^{NET} \cdot {\rm RADSWT},
1827  \]  \]
1828  or  or
1829  \[  \[
1830  {\bf RADSW} = \frac{g}{c_p \pi} {\partial \over \partial \sigma} F(cloudy)_{SW}^{NET}\cdot {\rm RADSWT} .  {\bf RADSW} = \frac{g}{c_p \pi} \p{\sigma} F(cloudy)_{SW}^{NET}\cdot {\rm RADSWT} .
1831  \]  \]
1832    
1833  \noindent  \noindent
# Line 1904  For a change in specific humidity due to Line 1847  For a change in specific humidity due to
1847  the vertical integral or total precipitable amount is given by:    the vertical integral or total precipitable amount is given by:  
1848  \[  \[
1849  {\bf PREACC} = \int_{surf}^{top} \rho \Delta q_{moist} dz = - \int_{surf}^{top} \Delta  q_{moist}  {\bf PREACC} = \int_{surf}^{top} \rho \Delta q_{moist} dz = - \int_{surf}^{top} \Delta  q_{moist}
1850  {dp \over g} = {1 \over g} \int_0^1 \Delta q_{moist} dp  \frac{dp}{g} = \frac{1}{g} \int_0^1 \Delta q_{moist} dp
1851  \]  \]
1852  \\  \\
1853    
# Line 1921  For a change in specific humidity due to Line 1864  For a change in specific humidity due to
1864  the vertical integral or total precipitable amount is given by:    the vertical integral or total precipitable amount is given by:  
1865  \[  \[
1866  {\bf PRECON} = \int_{surf}^{top} \rho \Delta q_{cum} dz = - \int_{surf}^{top} \Delta  q_{cum}  {\bf PRECON} = \int_{surf}^{top} \rho \Delta q_{cum} dz = - \int_{surf}^{top} \Delta  q_{cum}
1867  {dp \over g} = {1 \over g} \int_0^1 \Delta q_{cum} dp  \frac{dp}{g} = \frac{1}{g} \int_0^1 \Delta q_{cum} dp
1868  \]  \]
1869  \\  \\
1870    
# Line 2006  where $\rho$ is the air density, and $K_ Line 1949  where $\rho$ is the air density, and $K_
1949  \noindent  \noindent
1950  The drag coefficient for momentum obtained by assuming a neutrally stable surface layer:  The drag coefficient for momentum obtained by assuming a neutrally stable surface layer:
1951  \[  \[
1952  {\bf CN} = { k \over { \ln({h \over {z_0}})} }  {\bf CN} = \frac{ k }{ \ln(\frac{h }{z_0}) }
1953  \]  \]
1954    
1955  \noindent  \noindent
# Line 2042  The air/surface virtual temperature diff Line 1985  The air/surface virtual temperature diff
1985  \noindent  \noindent
1986  where  where
1987  \[  \[
1988  \theta_{v{Nrphys+1}} = { T_g \over {P^{\kappa}_{surf}} } (1 + .609 q_{Nrphys+1}) \hspace{1cm}  \theta_{v{Nrphys+1}} = \frac{ T_g }{ P^{\kappa}_{surf} } (1 + .609 q_{Nrphys+1}) \hspace{1cm}
1989  and \hspace{1cm} q_{Nrphys+1} = q_{Nrphys} + \beta(q^*(T_g,P_s) - q_{Nrphys})  and \hspace{1cm} q_{Nrphys+1} = q_{Nrphys} + \beta(q^*(T_g,P_s) - q_{Nrphys})
1990  \]  \]
1991    
# Line 2071  net surface upward longwave radiative fl Line 2014  net surface upward longwave radiative fl
2014  sea ice, $H$ is the upward sensible heat flux, $LE$ is the upward latent heat  sea ice, $H$ is the upward sensible heat flux, $LE$ is the upward latent heat
2015  flux, and $C_g$ is the total heat capacity of the ground.  flux, and $C_g$ is the total heat capacity of the ground.
2016  $C_g$ is obtained by solving a heat diffusion equation  $C_g$ is obtained by solving a heat diffusion equation
2017  for the penetration of the diurnal cycle into the ground (Blackadar, 1977), and is given by:  for the penetration of the diurnal cycle into the ground (\cite{black:77}), and is given by:
2018  \[  \[
2019  C_g = \sqrt{ {\lambda C_s \over {2 \omega} } } = \sqrt{(0.386 + 0.536W + 0.15W^2)2x10^{-3}  C_g = \sqrt{ \frac{\lambda C_s }{ 2 \omega } } = \sqrt{(0.386 + 0.536W + 0.15W^2)2x10^{-3}
2020  { 86400. \over {2 \pi} } } \, \, .  \frac{86400.}{2\pi} } \, \, .
2021  \]  \]
2022  \noindent  \noindent
2023  Here, the thermal conductivity, $\lambda$, is equal to $2x10^{-3}$ ${ly\over{ sec}}  Here, the thermal conductivity, $\lambda$, is equal to $2x10^{-3}$ $\frac{ly}{sec}
2024  {cm \over {^oK}}$,  \frac{cm}{K}$,
2025  the angular velocity of the earth, $\omega$, is written as $86400$ $sec/day$ divided  the angular velocity of the earth, $\omega$, is written as $86400$ $sec/day$ divided
2026  by $2 \pi$ $radians/  by $2 \pi$ $radians/
2027  day$, and the expression for $C_s$, the heat capacity per unit volume at the surface,  day$, and the expression for $C_s$, the heat capacity per unit volume at the surface,
# Line 2220  Thus, {\bf LWCLR} is defined as the net Line 2163  Thus, {\bf LWCLR} is defined as the net
2163  vertical divergence of the  vertical divergence of the
2164  clear-sky longwave radiative flux:  clear-sky longwave radiative flux:
2165  \[  \[
2166  \pp{\rho c_p T}{t}_{clearsky} = - {\partial \over \partial z} F(clearsky)_{LW}^{NET} ,  \pp{\rho c_p T}{t}_{clearsky} = - \p{z} F(clearsky)_{LW}^{NET} ,
2167  \]  \]
2168  or  or
2169  \[  \[
2170  {\bf LWCLR} = \frac{g}{c_p \pi} {\partial \over \partial \sigma} F(clearsky)_{LW}^{NET} .  {\bf LWCLR} = \frac{g}{c_p \pi} \p{\sigma} F(clearsky)_{LW}^{NET} .
2171  \]  \]
2172    
2173  \noindent  \noindent
# Line 2414  The surface stress velocity, or the fric Line 2357  The surface stress velocity, or the fric
2357  the surface layer top impeded by the surface drag:  the surface layer top impeded by the surface drag:
2358  \[  \[
2359  {\bf USTAR} = C_uW_s \hspace{1cm}where: \hspace{.2cm}  {\bf USTAR} = C_uW_s \hspace{1cm}where: \hspace{.2cm}
2360  C_u = {k \over {\psi_m} }  C_u = \frac{k}{\psi_m}
2361  \]  \]
2362    
2363  \noindent  \noindent
# Line 2426  number 10), and $W_s$ is the surface win Line 2369  number 10), and $W_s$ is the surface win
2369    
2370  \noindent  \noindent
2371  Over the land surface, the surface roughness length is interpolated to the local  Over the land surface, the surface roughness length is interpolated to the local
2372  time from the monthly mean data of Dorman and Sellers (1989). Over the ocean,  time from the monthly mean data of \cite{dorsell:89}. Over the ocean,
2373  the roughness length is a function of the surface-stress velocity, $u_*$.  the roughness length is a function of the surface-stress velocity, $u_*$.
2374  \[  \[
2375  {\bf Z0} = c_1u^3_* + c_2u^2_* + c_3u_* + c_4 + {c_5 \over {u_*}}  {\bf Z0} = c_1u^3_* + c_2u^2_* + c_3u_* + c_4 + {c_5}{u_*}
2376  \]  \]
2377    
2378  \noindent  \noindent
2379  where the constants are chosen to interpolate between the reciprocal relation of  where the constants are chosen to interpolate between the reciprocal relation of
2380  Kondo(1975) for weak winds, and the piecewise linear relation of Large and Pond(1981)  \cite{kondo:75} for weak winds, and the piecewise linear relation of \cite{larpond:81}
2381  for moderate to large winds.  for moderate to large winds.
2382  \\  \\
2383    
# Line 2483  input at the top of the atmosphere. Line 2426  input at the top of the atmosphere.
2426  \noindent  \noindent
2427  The heating rate due to Shortwave Radiation under clear skies is defined as:  The heating rate due to Shortwave Radiation under clear skies is defined as:
2428  \[  \[
2429  \pp{\rho c_p T}{t} = - {\partial \over \partial z} F(clear)_{SW}^{NET} \cdot {\rm RADSWT},  \pp{\rho c_p T}{t} = - \p{z} F(clear)_{SW}^{NET} \cdot {\rm RADSWT},
2430  \]  \]
2431  or  or
2432  \[  \[
2433  {\bf SWCLR} = \frac{g}{c_p } {\partial \over \partial p} F(clear)_{SW}^{NET}\cdot {\rm RADSWT} .  {\bf SWCLR} = \frac{g}{c_p } \p{p} F(clear)_{SW}^{NET}\cdot {\rm RADSWT} .
2434  \]  \]
2435    
2436  \noindent  \noindent
# Line 2674  If we define the time-tendency of Temper Line 2617  If we define the time-tendency of Temper
2617  \end{eqnarray*}  \end{eqnarray*}
2618  then, since there are no surface pressure changes due to Diabatic processes, we may write  then, since there are no surface pressure changes due to Diabatic processes, we may write
2619  \[  \[
2620  \pp{T}{t}_{Diabatic} = {p^\kappa \over \pi }\pp{\pi \theta}{t}_{Diabatic}  \pp{T}{t}_{Diabatic} = \frac{p^\kappa}{\pi}\pp{\pi \theta}{t}_{Diabatic}
2621  \]  \]
2622  where $\theta = T/p^\kappa$.  Thus, {\bf DIABT} may be written as  where $\theta = T/p^\kappa$.  Thus, {\bf DIABT} may be written as
2623  \[  \[
2624  {\bf DIABT} = {p^\kappa \over \pi } \left( \pp{\pi \theta}{t}_{Diabatic} + \pp{\pi \theta}{t}_{Analysis} \right)  {\bf DIABT} = \frac{p^\kappa}{\pi} \left( \pp{\pi \theta}{t}_{Diabatic} + \pp{\pi \theta}{t}_{Analysis} \right)
2625  \]  \]
2626  \\  \\
2627    
# Line 2697  If we define the time-tendency of Specif Line 2640  If we define the time-tendency of Specif
2640  \]  \]
2641  then, since there are no surface pressure changes due to Diabatic processes, we may write  then, since there are no surface pressure changes due to Diabatic processes, we may write
2642  \[  \[
2643  \pp{q}{t}_{Diabatic} = {1 \over \pi }\pp{\pi q}{t}_{Diabatic}  \pp{q}{t}_{Diabatic} = \frac{1}{\pi}\pp{\pi q}{t}_{Diabatic}
2644  \]  \]
2645  Thus, {\bf DIABQ} may be written as  Thus, {\bf DIABQ} may be written as
2646  \[  \[
2647  {\bf DIABQ} = {1 \over \pi } \left( \pp{\pi q}{t}_{Diabatic} + \pp{\pi q}{t}_{Analysis} \right)  {\bf DIABQ} = \frac{1}{\pi} \left( \pp{\pi q}{t}_{Diabatic} + \pp{\pi q}{t}_{Analysis} \right)
2648  \]  \]
2649  \\  \\
2650    
# Line 2715  and dividing by the total mass of the co Line 2658  and dividing by the total mass of the co
2658  \[  \[
2659  {\bf VINTUQ} = \frac{ \int_{surf}^{top} u q \rho dz  } { \int_{surf}^{top} \rho dz  }  {\bf VINTUQ} = \frac{ \int_{surf}^{top} u q \rho dz  } { \int_{surf}^{top} \rho dz  }
2660  \]  \]
2661  Using $\rho \delta z = -{\delta p \over g} = - {1 \over g} \delta p$, we have  Using $\rho \delta z = -\frac{\delta p}{g} = - \frac{1}{g} \delta p$, we have
2662  \[  \[
2663  {\bf VINTUQ} = { \int_0^1 u q dp  }  {\bf VINTUQ} = { \int_0^1 u q dp  }
2664  \]  \]
# Line 2732  and dividing by the total mass of the co Line 2675  and dividing by the total mass of the co
2675  \[  \[
2676  {\bf VINTVQ} = \frac{ \int_{surf}^{top} v q \rho dz  } { \int_{surf}^{top} \rho dz  }  {\bf VINTVQ} = \frac{ \int_{surf}^{top} v q \rho dz  } { \int_{surf}^{top} \rho dz  }
2677  \]  \]
2678  Using $\rho \delta z = -{\delta p \over g} = - {1 \over g} \delta p$, we have  Using $\rho \delta z = -\frac{\delta p}{g} = - \frac{1}{g} \delta p$, we have
2679  \[  \[
2680  {\bf VINTVQ} = { \int_0^1 v q dp  }  {\bf VINTVQ} = { \int_0^1 v q dp  }
2681  \]  \]
# Line 2765  and dividing by the total mass of the co Line 2708  and dividing by the total mass of the co
2708  \[  \[
2709  {\bf VINTVT} = \frac{ \int_{surf}^{top} v T \rho dz  } { \int_{surf}^{top} \rho dz  }  {\bf VINTVT} = \frac{ \int_{surf}^{top} v T \rho dz  } { \int_{surf}^{top} \rho dz  }
2710  \]  \]
2711  Using $\rho \delta z = -{\delta p \over g} $, we have  Using $\rho \delta z = -\frac{\delta p}{g} $, we have
2712  \[  \[
2713  {\bf VINTVT} = { \int_0^1 v T dp  }  {\bf VINTVT} = { \int_0^1 v T dp  }
2714  \]  \]
# Line 2830  The Total Precipitable Water is defined Line 2773  The Total Precipitable Water is defined
2773  given by:  given by:
2774  \begin{eqnarray*}  \begin{eqnarray*}
2775  {\bf QINT} & = & \int_{surf}^{top} \rho q dz \\  {\bf QINT} & = & \int_{surf}^{top} \rho q dz \\
2776             & = & {\pi \over g} \int_0^1 q dp             & = & \frac{\pi}{g} \int_0^1 q dp
2777  \end{eqnarray*}  \end{eqnarray*}
2778  where we have used the hydrostatic relation  where we have used the hydrostatic relation
2779  $\rho \delta z = -{\delta p \over g} $.  $\rho \delta z = -\frac{\delta p}{g} $.
2780  \\  \\
2781    
2782    
# Line 2843  $\rho \delta z = -{\delta p \over g} $. Line 2786  $\rho \delta z = -{\delta p \over g} $.
2786  \noindent  \noindent
2787  The u-wind at the 2-meter depth is determined from the similarity theory:  The u-wind at the 2-meter depth is determined from the similarity theory:
2788  \[  \[
2789  {\bf U2M} = {u_* \over k} \psi_{m_{2m}} {u_{sl} \over {W_s}} =  {\bf U2M} = \frac{u_*}{k} \psi_{m_{2m}} \frac{u_{sl}}{W_s} =
2790  { \psi_{m_{2m}} \over {\psi_{m_{sl}} }}u_{sl}  \frac{ \psi_{m_{2m}} }{ \psi_{m_{sl}} }u_{sl}
2791  \]  \]
2792    
2793  \noindent  \noindent
# Line 2859  is above two meters, ${\bf U2M}$ is unde Line 2802  is above two meters, ${\bf U2M}$ is unde
2802  \noindent  \noindent
2803  The v-wind at the 2-meter depth is a determined from the similarity theory:  The v-wind at the 2-meter depth is a determined from the similarity theory:
2804  \[  \[
2805  {\bf V2M} = {u_* \over k} \psi_{m_{2m}} {v_{sl} \over {W_s}} =  {\bf V2M} = \frac{u_*}{k} \psi_{m_{2m}} \frac{v_{sl}}{W_s} =
2806  { \psi_{m_{2m}} \over {\psi_{m_{sl}} }}v_{sl}  \frac{ \psi_{m_{2m}} }{ \psi_{m_{sl}} }v_{sl}
2807  \]  \]
2808    
2809  \noindent  \noindent
# Line 2875  is above two meters, ${\bf V2M}$ is unde Line 2818  is above two meters, ${\bf V2M}$ is unde
2818  \noindent  \noindent
2819  The temperature at the 2-meter depth is a determined from the similarity theory:  The temperature at the 2-meter depth is a determined from the similarity theory:
2820  \[  \[
2821  {\bf T2M} = P^{\kappa} ({\theta* \over k} ({\psi_{h_{2m}}+\psi_g}) + \theta_{surf} ) =  {\bf T2M} = P^{\kappa} (\frac{\theta*}{k} ({\psi_{h_{2m}}+\psi_g}) + \theta_{surf} ) =
2822  P^{\kappa}(\theta_{surf} + { {\psi_{h_{2m}}+\psi_g} \over {{\psi_{h_{sl}}+\psi_g}} }  P^{\kappa}(\theta_{surf} + \frac{ \psi_{h_{2m}}+\psi_g }{ \psi_{h_{sl}}+\psi_g }
2823  (\theta_{sl} - \theta_{surf}))  (\theta_{sl} - \theta_{surf}) )
2824  \]  \]
2825  where:  where:
2826  \[  \[
2827  \theta_* = - { (\overline{w^{\prime}\theta^{\prime}}) \over {u_*} }  \theta_* = - \frac{ (\overline{w^{\prime}\theta^{\prime}}) }{ u_* }
2828  \]  \]
2829    
2830  \noindent  \noindent
# Line 2897  is above two meters, ${\bf T2M}$ is unde Line 2840  is above two meters, ${\bf T2M}$ is unde
2840  \noindent  \noindent
2841  The specific humidity at the 2-meter depth is determined from the similarity theory:  The specific humidity at the 2-meter depth is determined from the similarity theory:
2842  \[  \[
2843  {\bf Q2M} = P^{\kappa} ({q_* \over k} ({\psi_{h_{2m}}+\psi_g}) + q_{surf} ) =  {\bf Q2M} = P^{\kappa} \frac({q_*}{k} ({\psi_{h_{2m}}+\psi_g}) + q_{surf} ) =
2844  P^{\kappa}(q_{surf} + { {\psi_{h_{2m}}+\psi_g} \over {{\psi_{h_{sl}}+\psi_g}} }  P^{\kappa}(q_{surf} + \frac{ \psi_{h_{2m}}+\psi_g }{ \psi_{h_{sl}}+\psi_g }
2845  (q_{sl} - q_{surf}))  (q_{sl} - q_{surf}))
2846  \]  \]
2847  where:  where:
2848  \[  \[
2849  q_* = - { (\overline{w^{\prime}q^{\prime}}) \over {u_*} }  q_* = - \frac{ (\overline{w^{\prime}q^{\prime}}) }{ u_* }
2850  \]  \]
2851    
2852  \noindent  \noindent
# Line 2921  The u-wind at the 10-meter depth is an i Line 2864  The u-wind at the 10-meter depth is an i
2864  and the model lowest level wind using the ratio of the non-dimensional wind shear  and the model lowest level wind using the ratio of the non-dimensional wind shear
2865  at the two levels:  at the two levels:
2866  \[  \[
2867  {\bf U10M} = {u_* \over k} \psi_{m_{10m}} {u_{sl} \over {W_s}} =  {\bf U10M} = \frac{u_*}{k} \psi_{m_{10m}} \frac{u_{sl}}{W_s} =
2868  { \psi_{m_{10m}} \over {\psi_{m_{sl}} }}u_{sl}  \frac{ \psi_{m_{10m}} }{ \psi_{m_{sl}} }u_{sl}
2869  \]  \]
2870    
2871  \noindent  \noindent
# Line 2938  The v-wind at the 10-meter depth is an i Line 2881  The v-wind at the 10-meter depth is an i
2881  and the model lowest level wind using the ratio of the non-dimensional wind shear  and the model lowest level wind using the ratio of the non-dimensional wind shear
2882  at the two levels:  at the two levels:
2883  \[  \[
2884  {\bf V10M} = {u_* \over k} \psi_{m_{10m}} {v_{sl} \over {W_s}} =  {\bf V10M} = \frac{u_*}{k} \psi_{m_{10m}} \frac{v_{sl}}{W_s} =
2885  { \psi_{m_{10m}} \over {\psi_{m_{sl}} }}v_{sl}  \frac{ \psi_{m_{10m}} }{ \psi_{m_{sl}} }v_{sl}
2886  \]  \]
2887    
2888  \noindent  \noindent
# Line 2955  The temperature at the 10-meter depth is Line 2898  The temperature at the 10-meter depth is
2898  temperature and the model lowest level potential temperature using the ratio of the  temperature and the model lowest level potential temperature using the ratio of the
2899  non-dimensional temperature gradient at the two levels:  non-dimensional temperature gradient at the two levels:
2900  \[  \[
2901  {\bf T10M} = P^{\kappa} ({\theta* \over k} ({\psi_{h_{10m}}+\psi_g}) + \theta_{surf} ) =  {\bf T10M} = P^{\kappa} (\frac{\theta*}{k} ({\psi_{h_{10m}}+\psi_g}) + \theta_{surf} ) =
2902  P^{\kappa}(\theta_{surf} + { {\psi_{h_{10m}}+\psi_g} \over {{\psi_{h_{sl}}+\psi_g}} }  P^{\kappa}(\theta_{surf} + \frac{\psi_{h_{10m}}+\psi_g}{\psi_{h_{sl}}+\psi_g}
2903  (\theta_{sl} - \theta_{surf}))  (\theta_{sl} - \theta_{surf}))
2904  \]  \]
2905  where:  where:
2906  \[  \[
2907  \theta_* = - { (\overline{w^{\prime}\theta^{\prime}}) \over {u_*} }  \theta_* = - \frac{ (\overline{w^{\prime}\theta^{\prime}}) }{ u_* }
2908  \]  \]
2909    
2910  \noindent  \noindent
# Line 2978  The specific humidity at the 10-meter de Line 2921  The specific humidity at the 10-meter de
2921  humidity and the model lowest level specific humidity using the ratio of the  humidity and the model lowest level specific humidity using the ratio of the
2922  non-dimensional temperature gradient at the two levels:  non-dimensional temperature gradient at the two levels:
2923  \[  \[
2924  {\bf Q10M} = P^{\kappa} ({q_* \over k} ({\psi_{h_{10m}}+\psi_g}) + q_{surf} ) =  {\bf Q10M} = P^{\kappa} (\frac{q_*}{k} ({\psi_{h_{10m}}+\psi_g}) + q_{surf} ) =
2925  P^{\kappa}(q_{surf} + { {\psi_{h_{10m}}+\psi_g} \over {{\psi_{h_{sl}}+\psi_g}} }  P^{\kappa}(q_{surf} + \frac{\psi_{h_{10m}}+\psi_g}{\psi_{h_{sl}}+\psi_g}
2926  (q_{sl} - q_{surf}))  (q_{sl} - q_{surf}))
2927  \]  \]
2928  where:  where:
2929  \[  \[
2930  q_* =  - { (\overline{w^{\prime}q^{\prime}}) \over {u_*} }  q_* =  - \frac{ (\overline{w^{\prime}q^{\prime}}) }{ u_* }
2931  \]  \]
2932    
2933  \noindent  \noindent
# Line 3025  q^{n+1} = (\pi q)^{n+1} / \pi^{n+1} Line 2968  q^{n+1} = (\pi q)^{n+1} / \pi^{n+1}
2968  \]  \]
2969    
2970    
2971  \subsection{Key subroutines, parameters and files}  \subsubsection{Key subroutines, parameters and files}
2972    
2973    \subsubsection{Dos and donts}
2974    
2975    \subsubsection{Fizhi Reference}
2976    
2977    \subsubsection{Experiments and tutorials that use fizhi}
2978    \label{sec:pkg:fizhi:experiments}
2979    
2980  \subsection{Dos and donts}  \begin{itemize}
2981    \item{Global atmosphere experiment with realistic SST and topography in fizhi-cs-32x32x10 verification directory. }
2982    \item{Global atmosphere aqua planet experiment in fizhi-cs-aqualev20 verification directory. }
2983    \end{itemize}
2984    
 \subsection{Fizhi Reference}  

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